Jobs at YipitData

Own and QA high-impact retail data products: design and run QA, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, improve automation and product reliability, and communicate methodology and limitations to clients.

Build and own end-to-end, production-grade full‑stack features across backend, frontend, data pipelines, and infrastructure. Collaborate with stakeholders to translate business problems into shipped software, drive cross-team initiatives, and improve tooling and code quality. Use AI coding tools daily to accelerate development and maintain reliability for customer-facing products.

As a Product Manager, you will drive the strategy, roadmap, and execution of data feed products, ensuring they meet both internal and external client needs. Responsibilities include P&L accountability, collaboration with cross-functional teams, overseeing data quality, and enhancing client delivery experiences, while contributing to product vision and market strategy.

Target and break into large enterprise accounts (>$100M software spend) using outbound prospecting (cold calls, emails, LinkedIn) to generate meetings with procurement leaders. Use modern sales tools, collaborate with sales leadership and enablement, refine messaging, and develop toward full end-to-end sales responsibility.

As a Research Analyst, you'll drive fundamental research for subscription-based data products, analyze large datasets, and collaborate with teams to offer insights and develop new products.

As a Senior Backend Engineer, you will implement ERP data connectors, upgrade backend APIs, maintain data storage, and ensure service stability. You'll collaborate with global teams to enhance data architecture and govern data integrity while utilizing technologies like Go or Python and cloud infrastructures.

Lead end-to-end marketing for YipitData's Investor business, owning demand generation, product go-to-market, customer marketing, campaign execution, and analytics. Partner with Sales, Product, Client Strategy, and Revenue Operations to drive pipeline, retention, and revenue. Build reporting dashboards, optimize performance across channels, and, over time, hire and scale the Investor marketing team.

The Senior Software Engineer will develop and maintain data systems and APIs, enhance data architecture, and ensure data governance while collaborating with global teams.

As a Tech Lead, you will own the technical direction of a B2B analytics platform, lead engineering teams, and ensure production reliability while collaborating with various stakeholders to translate business needs into technical solutions.

The Senior QA Engineer will develop test plans, handle automated and performance testing, manage defects, and collaborate with teams for project progress.

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.

The Senior Recruiter will lead high-impact recruiting efforts for the GTM organization, focusing on strategic searches across Sales, Marketing, Customer Success, and Strategy. Responsibilities include managing the full recruiting cycle, developing talent pipelines, enhancing candidate experience, and utilizing ATS systems effectively.

The Client Strategy Manager will manage client relationships, develop commercial strategies, and ensure client success through proactive engagement and support. This role includes account management, upselling, and enhancing client engagement with the firm's analytics services.

As a Data QA Associate, you'll manage data cleaning and quality assurance processes, transforming receipt data into business insights, collaborating with remote teams, and ensuring data consistency and quality.

The Data Operations Analyst develops custom product attribution based on client needs, utilizing tagging and machine learning; ensuring data mapping accuracy and project delivery.

Lead an end-to-end data domain: define processing and validation, build reusable methodologies and QA/monitoring systems, partner with product and engineering to set technical direction, onboard new datasets, apply AI/automation to reduce manual work, and mentor junior analysts to scale domain capabilities.

Lead and grow a data engineering team; design and operate end-to-end data platforms on cloud and Databricks; own architecture, pipelines (batch & streaming), performance, cost, governance, and roadmap; hire and mentor engineers and collaborate with data science and product teams.

The Account Development Manager will manage client relationships, drive client engagement, execute growth strategies, and develop commercial strategies for renewals and upsells.

Build and maintain end-to-end data pipelines using PySpark and SQL on Databricks/Delta. Establish data modeling and pipeline best practices, create AI-ready analytical datasets, troubleshoot pipeline issues, and collaborate with stakeholders to embed business logic and optimize reliability, efficiency, and performance.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.